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Whether you’re facing explosive growth or trying to manage your Cost of Services as you build out your customer facing organization, you know that you are going to be faced with real-world resource constraints as you fund and build a Customer Success function. And after all, you’re a responsible leader and this is 2013, so you know better than to just throw people at a problem. So how do you efficiently manage growth in a Customer Success organization while effectively empowering your customers?

In my last post, A Practical View of Your Customers, I introduced an approach for understanding and mapping your customers by revenue using a Pareto chart. While I focused that article on how to look at your customer segments based on revenue, I’d like to focus this article on where to draw the line for each segment and why. If you haven’t read the previous post yet, I’d suggest doing so now. If you’re familiar with Pareto principles, my prior post certainly isn’t rocket science. You may still want to read it, though, as I’ll be re-using a chart I introduced there to illustrate my points.

Customer Segmentation and Engagement Models

The First, High-Touch Segment

Unless your company is a rare blue unicorn and you have a completely homogeneous customer base, you’re going to have some distribution of current and potential revenue across that customer base. Creating a Pareto Chart will show you which of your customers make up the largest revenue contribution. While my hypothetical (but not uncommon) example in my previous post showed a top tier segment where 10% of the customers accounted for 45% of the revenue, your results may differ – possibly significantly. It is almost certain, however, that a minority of your customers will account for a majority of your revenue and very likely that a small tier will account for a significant percentage (greater than 30%). If this is the case, you have a great opportunity to create a premium service offering via Customer Success that will focus on retaining and growing those customers.

This tier of customers is incredibly valuable. You can afford to (and need to) provide them with some attention, and ensure that you have great two-way communication in place in order to both guide them as well as learn from them. If you’re in the early stages of building your Customer Success team, I’d suggest this first cut at determining how to build out this team:

Think about the key activities that are required to ensure your top tier customers are getting value from your product

Understand how much of a person’s time it will take to provide those activities

Multiply that time by the number of customers you have in your top tier, and then staff accordingly, understanding that your CSMs will likely be able to spend less than 100% of their time on the activities you just defined

Note that this is a bit of an iterative process, and you’ll be doing a few “reality checks” as you understand how much time is needed for your customers – and as a consequence, how many people will be needed to deliver the experience you want your customers to have. There truly is a combination of art and science to this process, and if you can’t afford to hire enough resources to adequately service the group you’ve identified as your top tier, then you have three options:

You can redefine and reduce the size of that tier then only expand it once you can adequately staff to support a larger number of top-tier customers;

You can redefine (reduce) the level of service you provide to your top-tier customers; or

You can introduce automation (customer success automation, marketing automation) to assist the CSM in managing the customer relationship

How much service and effort you provide to each customer is going to be specific to your offering. Once you’ve done your calculations, you’ll likely want to perform a reality check based on the Book of Business each CSM is projected to be responsible for. I’ve seen organizations where each CSM has a Book of Business of as little as $1M of annual recurring revenue and others where that number is closer to $10M… or more. Metrics and “standards” are still all over the map on this topic and are really dependent upon your industry and the level of service you need to provide to your customers. Early stage, highly-technical solutions will require more CSM effort than later stage “commodity” solutions. Whatever stage or solution you’re at, though, be sure that you’re creating a role that is going to be sufficiently engaged to help your customers achieve value.

A Second, Hybrid Segment (Optional, but likely)

Depending on your customer distribution, you may want to define a second segment of customers who still represent significant revenue, but are probably closer to a 1:1 ratio of percentage of customers to percentage of revenue. In the hypothetical example I provide, the second customer segment represents 20% of the customers and 30% of the revenue. Again, your mileage may vary; however if you have a second tier of customers that makes up a sizeable percentage of your revenue, then you can (and probably should) identify a less intensive, but still personal, level of relationship with them (perhaps less frequent interaction than tier one and perhaps assisted even further by marketing automation). By doing this, you now have created personal relationships with two segments of customers that likely cover a majority of your revenue, but only a relatively small minority of your customers. My example in the last post shows 30% of customers representing 75% of revenue. While my example data is hypothetical, I’ve seen a number of companies within +/- 10% of these ratios, especially in the B2B space.

So how many CSMs should you assign to this space?

A good reality check for the number of CSMs to assign to this group is to use your Book of Business per CSM as the great equalizer. You may have CSMs in group 1 covering 10-15 customers and $3M in ARR. In Group 2, with smaller customers , a CSM might need to manage 50-75 customers to cover $3M in ARR. Automation will play a key role here to help identify customers in need, customers at risk, and to trigger targeted communications to customers at the right time.

The Third, Highly Automated Segment

While you’ve likely covered a majority of your revenue base in the first two segments, you still have a long tail (actually a very long tail in cases like freemium) of customers who are using your services but – at least for the time being – provide you with very little revenue. This customer segment is certainly important, both from a numbers, lead generation, and future revenue perspective; however you can’t afford to provide them with the same level of service you provide to customers who are paying orders of magnitude more than they are per month, so what does automation for this segment look like?

Whether this long tail represents 300 or 300,000 customers, you’re going to benefit greatly from an automation solution (or solutions) that help you:

Identify customer usage patterns

Identify at-risk customers

Send appropriate communications to those customers based on behavior, triggers, or their lifecycle

Keep your entire customer base engaged by helping you connect with them in a relevant way

While the long tail doesn’t represent a majority of your revenue, both this segment and your second segment are going to contain customers who represent incredible upsell opportunities – if you do some analysis that will help identify them. If you spend the extra effort up front, you can also leverage marketing automation to target relevant messages to those customers based on their behavior, activity, and other usage metrics.

If your strategy is to land and expand, you’ll need to look everywhere for the expansion opportunities, not just in the top tier. And if you’re using analytics, segmentation and automation appropriately, you can drive meaningful action with the right customers, whether they’re in your “top” tier or in your long tail.

A few months ago I wrote a post about customer segmentation titled All Customers Are Equal, But Some Are More Equal Than Others. I graphically represented the concept of customer segments with a pyramid, because it was a simple and straightforward representation of the concept. When it comes down to actually segmenting your own customer base, though, and making decisions about how to service them, I’ve found the best way to do that is to use a Pareto Chart.

Figure 1: Pareto Chart of 2000 Hypothetical B2B Customers

The Chart Described

If you aren’t familiar with the concept, a Pareto Chart is great way to visualize how your revenue is distributed across your customer base and how much your largest customers contribute to your overall revenue.

The chart above came from a hypothetical set of 2,000 customers I created from data that I made-up to represent a typical B2B customer distribution curve. The grey portion of the Pareto Chart is actually a bar graph made up of 2000 data points in descending order. Each (very thin) bar represents a customer’s Monthly Recurring Revenue (MRR) and maps to the axis on the left – in MRR dollars.

The blue line shows the cumulative percentage of revenue represented by the customer base as it moves along the X axis and maps to the axis on the right – in percentage of total revenue.

Creating Your First Segment

The Pareto chart quickly shows you a couple of things:

How your customers are distributed

How many customers fall into each bucket so that you can efficiently allocate resources to manage a large percentage of your revenue base.

The image below takes this hypothetical (but not uncommon) B2B case and creates a first segment of customers. This segment happens to consist of approximately 10% of the customer base (It’s 200 grey “bars” wide, representing 10% of the 2000 bars in the graph) and approximately 45% of the revenue (the right edge of the green area intersects the blue “% of revenue” line at about 45%). You’ll also see that the MRR value at the right edge of the green area is approximately $5,000 – which represents the minimum MRR for a “Tier 1” customer. Again, these numbers are examples. The process for creating customer segments requires a little art to go with this science and is going to take some iterations to get right; however 10% of your customer base is a reasonable baseline number for a high-touch CSM organization. You may choose to make it larger or smaller for a number of reasons (which I’ll cover in a future post), but this framework is a good way to illustrate it and justify whether you’re covering a reasonable amount of your revenue base.

Figure 2: The First Segment

The Second Segment

Now that you’ve created a high-revenue customer segment that can justify a high-touch CSM, you might want to see whether it makes sense to cover another relatively small number of customers that still might represent significant revenue with a somewhat lower touch, but still personal, approach. Based on this customer distribution, you can see that a second segment can be created that consists of twice as many customers as the first segment, and in combination with the first segment gives you coverage for approximately 75% of monthly revenue.

Figure 3: The Second Segment

Pareto Charts can illustrate pretty clearly how much revenue is represented by each segment of customer as well as show the baseline MRR that can be used to define the “floor” of each segment. Figure 3 shows that in this hypothetical situation, 75% of the revenue is represented by approximately 30% of the customer base, with an MRR of $1,700 and above.

So Now What?

Now that you have a framework for segmenting your customers, you can optimize your investment in your CSM function. In this example, the first segment of customers represents significant revenue that can justify high-touch named CSMs who can engage with customers in a personal, frequent, and customized manner. The second segment consists of roughly twice as many customers and a little over half the overall revenue of the first segment, so the amount of engagement per customer that can be justified for each CSM is significantly lower. The third segment represents approximately 3/4 of total customers yet only 1/4 of total revenue and can be effectively managed with Customer Success Automation and Marketing Automation. I’ll discuss how to address these three very different customer segments in more detail, and how Customer Success Automation applies across all three in a future post.

Last week I was having coffee with a friend who is a technologist with a background in journalism, and he asked me the following question: “Do you think the subscription model is dead?”

I answered in the context of software with “No, I think it’s only starting. I actually think it’s going to eat the perpetual license model for lunch. Why do you ask?”

He answered in the context of media subscriptions with “Well, as good, free content continues to proliferate, then why on earth would people be willing to pay for it?”

Then it hit me (well actually, two things hit me: the first being that I should understand the context of someone’s question before I answer it, but the second one was the bigger “aha”): As much as SaaS companies talk about subscription management, and as much as everyone who gets their news from Twitter (like I do) loves to flog the newspaper industry about its impending death, there’s an incredible lesson here about subscriptions, and I heard myself say it when I answered his second question:

“People will pay for content, or anything, for that matter, as long as the incremental value of that content when compared to the free stuff justifies the expense. Personally, that means I’m willing to spend $99/year on The Economist or Harvard Business Review, but not $23 per month on the Wall Street Journal or $8.75 per week for the NY Times.”

…and the bigger lesson here is that the principle of value holds true across the board in the subscription world, whether you’re talking about software or media, or information. The more what you’re selling becomes commoditized (and information has now become the poster child for commoditization), the more you need to ensure that you understand whether your customers are getting value from what you’re delivering. If they don’t, you need to do something about it, or they won’t be your customers for long.

If you’re an early stage company, you’re likely focused on proving that your solution is better than doing things manually or better than using the solution that you’re disrupting. The role of Customer Success is somewhat “missionary”, just as the sales role is. There’s quite a bit of evangelizing and proving that your solution is better than no solution, and you’re measuring adoption not just for the sake of your product’s adoption, but for the sake of validating that the market sees value in a type of solution like yours. In essence, you’re selling against the status quo.

If you’re a later stage company, on the other hand, your Customer Success function is more focused on proving that your specific product is delivering value and less about needing to convince the marketplace that they need a product like yours. The tricky part for a later stage company, however, is that unless you can differentiate your offering (product and services), you risk being commoditized. And commoditized solutions are very tricky to service because the only differentiator in the customer’s mind is price, and competitors end up trying to poach each others’ customers based on lower prices in a race to the bottom. That’s obviously a really crappy place to be, so if your product doesn’t differentiate itself, you really need to differentiate your solution based on the service you deliver. Your Customer Success mission should achieve the following:

Empower your customers and provide them with value so that they have no legitimate reason to talk to your competitors or question why they’re paying what they are paying for your solution;

Understand which customers aren’t getting value so that your organization can react appropriately. Do this quickly and frequently so that you’re understanding potential customer issues and patterns before they become deep-rooted;

Understand which customers are either strong potential brand advocates or which ones are candidates for additional products or services and use both of those categories of customers to continuously “de-commoditize” yourself.

I guess there’s one more realization that I came to the other morning, which is that I can’t even have a cup of coffee anymore without thinking about Customer Success.

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As the old saying goes: “You only have one chance to make a first impression”. If you want to increase the likelihood of success for the deployment and adoption of software, you need to make that first impression while your customer is still excited about their purchase decision. It holds true for enterprise software, B2C software, and everything in between, even though complexity and timeframes differ for each of those categories. In the world of SaaS, the post-sale journey to adoption and value can make or break a company.

So how do you effectively manage your deployments so that you’re: A) maintaining that momentum; and B) providing a quality customer experience that is helping them get a return on their investment in your solution? A great metric to use is Time To Value (TTV). Every solution is going to have it’s own onboarding process which can be as simple as an in-app wizard or as complex as a data integration and product configuration/customization project done by a Professional Services team. In either case, a reasonable target TTV should be measured in days or weeks (rather than months), depending on the complexity of the product and the onboarding process. Even for complex enterprise solutions, you should create a phased deployment where you can measure initial value in 4-6 weeks. Loss of momentum in an implementation can create an incredible amount of pain for enterprise software deployments. Too often, the perceived/expected value in an enterprise software deployment looks like the Gartner Hype Cycle where customers fall into the equivalent of the trough of disillusionment (and frustration) prior to seeing any value from their solution. There was a surprising amount of tolerance for this in the world of perpetual licenses. In the SaaS world, however, …not so much:

It should really be a much smoother and consistent curve of increased value demonstration (with aligned customer expectations) over time.

So how do you minimize time to value (TTV) for your customers, manage their expectations through the deployment cycle, and avoid the equivalent of the “trough of disillusionment”?

Step 1: Identify the unit of measure for value and set a quantifiable objective

Unless you define a “currency” by which you will measure value, you won’t know whether you’re delivering it. In some cases, adoption/usage may be used as a proxy, but to the extent that you can use a metric that your customer will use to measure the financial impact of your solution, start with that unit of measure. Examples for different types of solutions include:

increased overall revenue

larger basket size (for e-commerce transactions)

higher customer lifetime value

higher conversion rates

quicker time to transaction

lower cost per transaction

Even for a single given solution, different customers may measure value in different ways, so it’s important to connect with them to understand their specific objectives that will justify the time, effort, and funding they’re allocating to your solution. You’re getting their resources because you can solve a problem for them. Figure out how they’re justifying their investment in your solution and use the same currency to measure value.

Step 2: Identify the phases for delivering that value

Even if your solution can provide an order of magnitude return on investment, don’t try to get there all at once. Provide quick wins for your customers by phasing your deployment. Don’t try to deploy to the entire enterprise (or market) at once. Pick a department or small, logical group, where you can prove adoption and value, then continue to move forward with the additional momentum you’ve created from the internal user base you just identified. Your objective should be to get a customer advocate/thought leader to stand up in under 60 days and say “look at the value we’ve gotten from this solution. We need to roll this out to a broader group.” If your strategy is to land and expand, understand that you haven’t really landed until you’ve proven value.

Providing quick wins not only keeps the momentum going, but it also provides a healthy deployment model where you’re interacting with your customer on a frequent basis and continuously validating that you’re proceeding according to plan. Without frequent checkpoints, customer expectations and deployment realities can diverge quickly. The most common reason I’ve seen behind runaway or at-risk projects has been this disconnect between expectations and reality due to inadequate interaction and communication. The longer the time period between conceptual agreement and validation, the higher the likelihood that the end result will not be what the customer expected. Improving Time To Value will increase your chances of success.

Step 3: Execute and Manage(!) according to that plan.

This one might seem obvious, but execution is key. If deliverables aren’t met, understand why… and quickly. Break your implementation process into stages and understand which of the stages are creating friction/delays. In many cases, if you’re suffering from slow deployments, it’s primarily because of one or two key aspects of your implementation process, not all of them. Even in cases where the entire process needs work, by breaking it down into stages and seeing which of the stages are causing the biggest problems, you can quickly understand how to prioritize your activities around improving the deployment process. Customer Success requires constant iteration, listening, and learning from your customers.

In some cases, implementation delays are seemingly due to lack of responsiveness or loss of momentum on the part of your customers. Re-think this problem and see if there’s a way that you can restructure the deployment process so that you’re being more prescriptive for your customers and not requiring them to do things that take so much time and effort. I recently came across one example with a company that provided configuration options for custom reports in their new social analytics product. As part of their implementation process, they would ask customers to provide them with the top 4 items they wanted to see in their custom reports. Enterprise customers would iterate for weeks trying to get internal consensus on those 4 items, delaying the deployment, and delaying the time to value for customers. The solution: create 4 prescribed reports as defined by the implementation consultant, based on their knowledge of the customer as part of Phase 1 deployment; then allow the customer to modify those reports in Phase 2.

Good social networking and B2C companies really get the importance of Time To Value. They’ve sped up adoption and reduced time to value by implementing sign-up wizards as part of the enrollment process. By the time a new customer has finished creating a new account on Facebook, LinkedIn, or Instagram, they’ve been prompted to import contacts from their address book or other social networks in order to be positioned to get value immediately. In a previous life I ran deployments for an enterprise social networking technology and as part of our implementation process, we “bootstrapped” user accounts so that every user had profiles built on Day 1 that incorporated expertise from their previous 90 days of activity. Look at your implementation process to determine whether there are any similar opportunities to prescribe/recommend configuration options to your customers or speed system readiness for your customers.

Momentum is incredibly powerful. By optimizing your deployments for Time To Value, you can maintain, and even increase that momentum to create successful, loyal customer relationships. That, in turn, will lead to a shorter TTR (Time To Reference) …but that’s a whole other metric!

In my last post, I introduced the concept of an Effectiveness Model as a framework for engagement with your customers. I introduced it in the context of four other steps to delivering value, but since it’s so fundamental to value delivery, I’d like to drill down on what it is and why it’s so important:

The Concept

The Concept is straightforward. As a provider of a solution, you should be doing more than just throwing software over the transom to your users. In fact, as a SaaS provider, you need to be proving value to them on an ongoing basis. That’s today’s reality. If you don’t, you risk losing your customers to competitors who will. Harsh, but true. Providing a framework for mapping your customers’ progress, comparing their behavior (and results) to “best in class” companies, and showing a path of progress to best practices will help your customers remain engaged with you. The idea isn’t new. The “Maturity Model” concept has been around for years in a heavier weight format, and while more complex models and engagement levels apply in B2B, B2C solutions can also benefit from defined models that encourage additional types of usage and provide your customers with a roadmap to become more effective at using your product.

In the image above, each box represents a stage in an example Effectiveness Model for CRM. The bullet points next to the boxes each represent behaviors representative of each phase. The process of creating a maturity model for your industry and solution isn’t complicated, but it isn’t just something you can churn out quickly without some careful thought.

Identify 3-5 phases that are indicative of customers’ implementation of your technology. You may want to start with the bookends. For your first phase, identify the basics that someone absolutely needs to implement in order to get value from your application. For your last phase, identify what the absolute, best-in-breed, thought leaders who have, or will implement, your type of technology are doing. Then map out 1-3 interim phases that are indicative of how companies would progress through the phases. The CRM Effectiveness Model I put together above is an example of what that might look like.

The concept is simple. Getting it right, however, will take iterations, critical review, and more iterations.

The Name (Effectiveness vs Maturity)

While “The Industry” has traditionally referred to models like this as Maturity Models, I’ve stopped using that term in customer interactions and internally. I was once in a meeting with a large, strategic enterprise customer and presented the concept of a “Maturity Model” that my team and I had created. I thought nothing of it for a split-second, as these types of things had been called Maturity Models for years. My team and I had spent a good amount of time developing and iterating on a model specific to my company’s industry and showed them characteristics of “mature” vs “less mature” companies. As I listened to the words come out of my mouth, however, and observed my customer’s body language, I realized that the term “maturity” sounded arrogant and condescending. From that point on, I’ve referred to these as Effectiveness Models given that we’re simply trying to make our customers more effective. It’s ok for me to use the term “maturity” when talking to my kids about assuming more responsibility as they get older. It isn’t ok for me to imply to my customers that they are immature because they aren’t using automation and deep analytics. Trusted advisor trumps arrogant vendor. Every time.

Giving Context to Your Customer Communications

Your customers are busy. They’re struggling with priorities just as you are. Whether you know/like it or not, you’re competing for their attention every time you reach out to contact them. I think any customer facing team needs to be aware of two golden rules: 1) Make sure the customer goes in to the call looking forward to getting value from their interaction with you; and 2) Make sure you’ve delivered that value by the end of the interaction so that they are looking forward to their next meeting with you. An Effectiveness Model sets you up for success. Your conversations with your customers are framed around objectives that you’ve set out with them. Your standing meetings and conversations with them can then be framed around what they’re doing (and how you can help them) to make progress.

The Value of Demonstrating Progress

There’s always a need to justify ROI, and to the extent you can do it with hard data, by all means, continue to do so in a way that is meaningful to your customers: Point out how many transactions they’ve performed in your system; if there’s a way of quantifying end objectives, like e-commerce transactions that have resulted from use of your application, then be sure to communicate those. In addition to those concrete numbers, or in cases where the concrete numbers are difficult to capture, it’s important to show your customers progress towards stated objectives. The Effectiveness Model provides a picture and path with clearly defined behaviors and objectives to map that progress. You can use this as a way to both map progress over time as well as identify activities and strategies to achieve the next phase of Effectiveness. Demonstrable progress, together, is a great foundation for a loyalty-based relationship.

An Opportunity to Position Key Features of Your Solution

As you create your industry/company’s specific Effectiveness Model, you have an opportunity to define how key features in your product can help your customers advance along the model. Be extremely careful, however, to avoid being overly self-promotional here or to “force-fit” your features into the model. An Effectiveness Model is just a tool to help advance a trust-based relationship with your customer. The model needs to be genuine and in your customers’ best interests. The reality is that if you have a great product and if you understand your customers, you can make some wonderful, insightful recommendations for them that will provide them with significant benefits, increase their use of your product, and make them more loyal in the process.

If you’ve been using an Effectiveness Model with your customers, I’d be interested in hearing about your learnings and feedback from them. If not, what have been your obstacles to developing one? Send me a dm on Twitter: @nfranco. Thanks!

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The funnel has been used for decades to model the journey a customer takes during the sales cycle. While it is still very effective as a forecasting tool, it falls short as an effective model of the overall customer journey, especially in the context of recurring revenue customers.

The cultivation process for identifying and processing new leads, then moving them through the steps to an initial commitment to your product is still best modeled by a funnel, and most of the common sales methodologies to date only support a funnel metaphor. I get it. Going though the qualification process and filtering a bunch of unqualified leads to qualified leads to qualified suspects and so on through the process is best illustrated and managed as if all these were going through a funnel with an expected conversion rate at each stage of x%, y%, and z%. In a world centered around new customer acquisition, this seems like a pretty good metaphor and it also helps provide forward visibility and predictability into new revenue for somewhat mature organizations; however when it comes to: A) capturing the journey once someone becomes a customer, especially one with multiple transactions; and B) predicting recurring revenue from an existing customer base, the funnel metaphor doesn’t work.

New Business is Only the Beginning

There is a strong tendency, even in the world of SaaS, to look at all revenue the same way. With any recurring revenue model, the focus needs to shift from a sales-centric perspective to a customer-centric perspective. Again, I’m not trying to minimize the importance of sales and new customers, or the predictability and management of that revenue stream. New customers and new revenue are vital to the growth and success of any organization. They just aren’t the end game of a sustainable recurring revenue business. They’re only the beginning.

So if the funnel isn’t the right metaphor for ongoing customers, what is? Some great minds have spent considerable time and effort on this problem and have come up with some good alternatives as a starting point.

Earlier this year Brian Solis wrote a blog post detailing a concept from his two most recent books about how the funnel no longer represents the customer journey, and especially from a digital marketer’s perspective, he isn’t alone. He cites work done by McKinsey four years ago based on research of 20,000 consumers identifying the customer decision journey as circular, with an outer loop representing “active exploration” and an inner “loyalty loop”. Both of these works, as well as Google’s Winning the Zero Moment of Truth highlight the recurring nature of the customer journey. They also key in on the important concept that the experience of your existing customer base will influence the purchase decisions of your future prospects. Brian Solis and The Altimeter Group’s model maps the following steps into a recurring elliptical path:

Awareness

Consideration

Evaluation

Purchase

Experience

Loyalty

Advocacy

The Funnel Has Revenue All Backwards

A funnel implies that significantly less revenue comes “out” of the funnel than entered the funnel in the form of leads – as shown in the image below. Again, this is a good assumption when managing and forecasting new business.

However, for an existing customer base in a healthy growing business with a good “land and expand” strategy and execution, the revenue that comes out of every cycle through the ellipse for the overall customer base should actually increases as a result of up-sells and cross-sells – as shown in the next figure.

Yes, some customers will (gulp) churn; however with a healthy business model and a good upsell/growth model and “land and expand” strategy, this net revenue should increase for your installed base of customers. Seth Godin, in his ebook Flipping the Funnel, as well as Joseph Jaffe, in his book Flip the Funnel, both discuss how you can use your existing customer base as advocates to market to additional prospects.

Are Rumors of the Funnel’s Death Greatly Exaggerated?

I don’t believe the funnel is dead. I think it still serves a purpose for predicting revenue and conversions, especially for new business. From a marketer’s perspective, however, and when trying to manage an existing customer base, the metaphor falls way short. The continuous elliptical path provides a much more realistic model for the customer journey and influence path. The next step is in applying metrics to the elliptical path in order to forecast recurring revenue so that it can be as effective as the funnel as a forecasting tool. Hmmm… I bet that would make a good topic for a blog post.

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Good Customer Success teams are analyzing data in order to understand the characteristics of their customers.

Great Customer Success teams are analyzing the right data in order to understand the characteristics of their customers.

Nowhere is analyzing the right data more critical than in understanding the early warning signs of at-risk customers. In generating awareness for this Thursday night’s CSM Forum Event: Detecting the At-Risk Customer Relationship, Mikael Blaisdell points out in his most recent blog post the one certainty behind at risk customers: “A customer that is not getting the desired level of measurable value out of their relationship with your company is one that is surely headed for the exit door.” I couldn’t agree more… or sooner.

In my last post, I indicated that the primary objective for a CSM organization should be to ensure that a customer is getting value from the implementation of your company’s solution. The CSM organization, whether highly personal, highly leveraged, or highly automated, needs to know which customers are at risk due to a lack of demonstrated value. Most organizations try to identify indicators of risk.

Generic Indicators: The Lowest Common Denominator

There’s one great thing about generic indicators of risk, such as system login/usage trends, support cases opened, and NPS values: Everyone can relate to them. There is almost always a correlation between one ore more of these factors and the level of churn risk associated with a customer, so everyone knows that they’re relevant. The problem with most of these indicators, however, is that they don’t always provide you with an early enough warning to allow you to take action that will save the customer, and in some cases, there isn’t even a cause/effect relationship between these criteria and churn. By the time most of this data is available, the customer knows they have a problem, and in some cases (like NPS) the customer has already gotten to the point of communicating it to you. In the case of usage metrics, I recently spoke with an executive who came from a financial services company. She told me they initially looked at usage data to determine which customers were at risk; however when they dug deeper and looked at the process that customers who defected went through, it was clear that by the time usage had declined, the customer had already run a month in parallel on a competitor’s solution and had already migrated off of theirs. Horse gone …no need to close the barn door.

Getting Beyond the Generic and Going Upstream

Really understanding whether a customer is getting measurable value from your solution requires that you look at indicators that are specific to you and to them. Think about your key selling points. Establish a Value Roadmap that you plan out with your customers and help them measure progress on a regular basis. This can be done with CSMs in a high touch environment or with system metrics and drip campaigns for low touch / high volume customer relationships. For example, if you offer a digital marketing solution, help your customers benchmark their existing conversion rates, then set goals and objectives for improvement and measure progress against those goals. If they aren’t achieving those objectives, then get out ahead of the problem. Do what you can to make them successful on your solution. Especially in the case of low-touch / high-volume deployment models (think B2C SaaS), great products will have relevant metrics reporting and prescriptive recommendations built in. Your offering shouldn’t just be about creating a technical solution to a problem, it should be about helping your customers get better at solving that problem with your offering. Keep in mind that your full “offering” includes product, services, and additional company interactions. Think about applying marketing automation principles for your installed base where the overt goal isn’t conversion, but successful use of your solution.

Also look at other data you have that might either indicate or result in a poor customer experience:

Have you had any recent system performance issues? If so, which customers were logged on at the time?

Have any of your key customers recently started following or connecting to your competitors on social media?

Are they not engaging with your drip customer marketing campaigns even though you’re sending them relevant content?

Are they not implementing the recommendations your team or the system has been providing on how to be more effective with your solution?

Are Generic Indicators Useless?

No. Absolutely not. And in many cases, they can still be useful as early warning indicators, especially in combination with other indicators. Every company, however, is going to need to take a good, hard, honest look at their own data to really understand which elements are early indicators – in their world – and which elements are simply correlated, but might be able to provide them insight on the trajectory of the customer relationship once they’ve been identified as “at risk” and a plan of action is put in place.

What early warning signs have you identified that are specific to your business and how have you used them to: 1) address the existing at-risk customers in the short term; and 2) and put a proactive plan of action into place to keep those issues from affecting other customers in the future?

Like this:

With all the Orwellian quotes from 1984 being tossed around as a result of PRISM, I thought I’d use one from his other book to describe the paradox of customer service for those of us who have ever supported a large and diverse B2B customer base. How do you provide a *great* experience for all of your customers in a scalable manner while creating something truly exceptional for your high value customers?

Well, first, you need to understand your customers – and while it’s actually not that uncommon for many startups in the SaaS space to have very good aggregate metrics such as CAC (Customer Acquisition Cost), Conversion Rates, etc., many companies don’t necessarily have individual customers very well segmented into logical groupings of actual and strategic value to the organization. It’s ugly, but it’s true, and it’s because a number of startups have gone through a growth process that looks something like this:

1) Invest in product and build it;

2) Invest in sales and grow the customer base;

3) Realize that the growing customer base is now large enough that it needs to be proactively managed and scramble like crazy to get the recurring revenue base under control.

Customer Segments

If you’re at this stage, getting things under control and categorized can actually be pretty straightforward. It just takes some thought, focus, and basic analysis. I’ve blogged about some of the technologies that are emerging in the space of revenue renewal management or Customer Success Automation. The reality, though, is that most SaaS companies, especially early stage ones, don’t yet have an analytics or Customer Success Automation solution to provide them with good insight into their customer base using real data-driven scoring and early warning systems across all customers. This post focuses on how to segment customers in the short term using basic data that you already have on your existing customer base (MRR, ACV, CLV, plus some other identifier for “strategic” accounts) …and it starts with the 80/20 rule.

The Top Tier: The “Most Equal”

While it may not be exactly 80/20, the reality is that in the vast majority of B2B SaaS companies, some small percentage of customers will represent a very large percentage of their revenue. Those customers are very high value and need to be treated as such. Create executive relationships and multiple touch points. Invest in them. Meet them face to face. Get to know them. Involve them in your business. Provide detailed monthly or quarterly business reviews that give them an indication of progress against stated objectives that you’ve worked out with them in advance. Determine the set of services you should be providing to this tier of customer and identify the amount of time it will take on an ongoing basis for your CSMs to provide those services to a model customer, then understand how many customers you can reasonably and consistently service given that time requirement… Congratulations, the laws of time and space just helped you create your first cut at your top customer segment.

Until you add more trained, senior, CSMs to your team or modify the level of service, you shouldn’t try to service more customers than you can at this level. If you over-commit, you risk missing on delivery expectations and you’ll leave your customers, er, less than satisfied. That may sound obvious, but getting from today’s reality to tomorrow’s desired state needs to be carefully managed. Next, determine how many customers you would like to see getting that level of service and either staff up your CSM team or pare back your service offering slightly (or some combination of both) in order for your needs and reality to align. Whatever number you come up with, you will need to justify it financially and take it into consideration when calculating your cost of services. A good initial target to shoot for if you’re a B2B SaaS company is to get 40% of your revenue into this bucket. In many cases it will be represented by fewer than 10% of your customers. Your mileage may vary, of course; however a reasonable range seems to be 1/3 to 1/2 of revenues represented by this customer tier for B2B SaaS companies.

The Second Tier: “The Most Leveraged”

While a high touch model works for that small percentage of customers who represent between 1/3 to 1/2 of your revenue, the law of diminishing returns takes over quickly and that model won’t scale to service the rest of your customer base. In this next tier, each CSM will handle significantly more customers (sometimes up to 10x more) than their “Top Tier” counterparts and they will need automation in order to be effective.

Try to identify useful data that you can extract from your systems, and automate its delivery to your customers via Customer Marketing and drip campaigns that are “signed” by the CSM. Compare that customer’s data against relevant benchmarks or aggregate data from the rest of your customer base. The more you can automate the heavy lifting and position your CSM as the expert who can provide some context, insight, and recommendations around the data presented, the more you’ll position your Customer Success Managers for success.

The Third Tier: “The Most Scalable”

Some percentage of customers, (in many companies this group might represent the majority of them) are not going to generate revenue sufficient enough to justify the cost of a high-touch relationship – especially with respect to proactive communication with customers. In order to support this tier of customers, a company needs to build out great self-service tools, including a self-service portal and an excellent customer marketing program… and they need to have a product offering for this tier that is intuitive and continuously improved as a result of customer feedback. Companies like MailChimp and ZenDesk are poster children in this space for what to do and how to do it. They provide great content. They also understand that many of their existing customers interact with their company primarily online, so they focus on creating a powerful, bonding, consistent online experience for their customers. Philosophically, they don’t see a “low touch” model as “low service”. They see it as a way to create a consistent, powerful, engaged relationship with their customer base – at scale. Understanding the importance of getting the product experience right, they also constantly listen to customer input, concerns, and challenges and respond by continuously making their product easier to use, more prescriptive, and less support-intensive.

While every company’s distribution of customers across these segments will vary with respect to percentage and number, and while your specific circumstances might require one more (or fewer) segment; understanding and segmenting your customers will help you focus on taking the right steps to provide the right level of service to each of them and create a great experience across all of them.

How have you segmented your customer base and what challenges have you faced in the process?